Hidden Markov Random Field Model - Inferring Gene-Disease Association by an Integrative Analysis of eQTL GWAS and Protein-Protein Interaction data
-
Updated
Mar 26, 2019 - R
Hidden Markov Random Field Model - Inferring Gene-Disease Association by an Integrative Analysis of eQTL GWAS and Protein-Protein Interaction data
Natural language processing of Gene Expression Omnibus data
Tool for integrative gene-based association analysis using GWAS summary stats
An unsupervised approach for the integrative analysis of single-cell multi-omics data
The statistical utility for RBP functions (SURF)
Code for Walker, Saunders, Rai et al., (2021).
A Python package for metabolite enrichment analysis.
A Decomposition-based Canonical Correlation Analysis for High-dimensional Datasets (JASA-20 paper)
🕸 Network-based multi-omic integration of metabolomics data.
MATLAB and R Code for sparse GCA
Bi-order integration (in silico multi-omics data) of single cell RNA sequencing, single cell ATAC sequencing, spacial transcriptomics and CyTOF data
Colocalization analysis of genetic association signals
Penalized regression for multiple types of many features with missing data using expectation-maximization (EM) algorithm.
TCGAbiolinks
MONTI is a tool for analyzing large multi-omics cancer cohort data in association with clinical featuers
Repository for the MetaBridge Shiny app.
Add a description, image, and links to the integrative-analysis topic page so that developers can more easily learn about it.
To associate your repository with the integrative-analysis topic, visit your repo's landing page and select "manage topics."